The pathway analysis demonstrated significant enrichment in the positive regulation of transcription in the DEGs coding for RNA polymerase II promoter, plasma membrane and chromatin binding pathways in cancer

Ewing's sarcoma (ES) is the second most common bone tumor among children and adolescents worldwide. However, the genes and signaling pathways involved in ES tumorigenesis and progression remain unclear. The present study used two gene‐expression profile datasets (GSE17674 and GSE31215) to elucidate key potential candidate genes and pathways in ES. Differentially expressed genes (DEGs) were identified and a functional enrichment analysis was performed. A protein‐protein interaction (PPI) network was constructed, and the most significant module in the PPI network was selected from the Search Tool for the Retrieval of Interacting Genes/Proteins database. A total of 278 genes were identified by comparing the tumor samples with non‐cancerous samples; these included 272 upregulated and 6 downregulated genes. The pathway analysis demonstrated significant enrichment in the positive regulation of transcription in the DEGs coding for RNA polymerase II promoter, plasma membrane and chromatin binding pathways in cancer in general. There were 269 nodes and 292 edges in the PPI network. Finally, MYC, IGF1, OAS1, EZH2 and ISG15 were identified as the hub genes according to the degree levels. The survival analysis revealed that EZH2 is associated with a poor prognosis in patients with ES. In conclusion, the DEGs, associated pathways and hub genes identified in the present study help elucidate the underlying molecular mechanisms of ES carcinogenesis and progression, and provide potential molecular targets and biomarkers for ES. Introduction Ewing's sarcoma (ES) is the second most common primary bone tumor among children and adolescents worldwide (1). In recent years, with the increase in ES research, significant prog‐ ress has been made towards the diagnosis, treatment, as well as prognosis of this disease. The current standard treatment for ES involves a five‐drug chemotherapy regimen (vincristine, doxorubicin, cyclophosphamide, ifosfamide and etoposide), and local resection or radiation therapy, or both (2). Although these treatments improve the survival rate of patients, the high rates of recurrence and metastasis in patients with ES neces‐ sitate the urgent development of new diagnostic strategies and therapeutic agents to improve patient prognosis. As the molecular mechanisms of ES tumorigenesis and progression are not yet entirely understood, there remains to be a number of unresolved issues in the diagnosis and treatment of ES. New ES‐associated technologies, as well as drugs, have emerged, but they did not meet the clinical standards. Therefore, it is essential to identify new genes and pathways associated with ES tumorigenesis and patient prognosis, in order to help unravel the relevant underlying molecular mechanisms, and to help discover novel diagnostic markers and therapeutic targets. Bioinformatics is a relatively new interdisciplinary subject that emerged in the late 1980s alongside the launch of the Human Genome Project. It reflects the permeation and inte‐ gration of biology, computer science, mathematics, physics (3) Through the acquisition, processing, storage, retrieval and analysis of experimental biological data, one achieves the purpose of interpreting the biological meaning and mecha‐ nisms underlying the activities in question from within the data. With the rapid development of microarray technology and bioinformatic analyses, microarrays are being used extensively for detecting gene expression levels, particularly in seeking differentially expressed genes (DEGs) (4). The application of microarrays has produced a large amount of data, which have been uploaded and stored in public databases. The use of microarray databases allows the identification of thousands of genes in ES, which can be utilized to screen for more molecular biomarkers. In the present study, two microarray datasets from the Gene Expression Omnibus (GEO) database (5) were down‐ loaded and analyzed in order to investigate the characteristics of the ES genomic expression profiles, as well as to screen Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways JINMING ZHANG1*, YAO ZHANG2*, ZE LI3, HONGZENG WU1, JIANJUN XUN1 and HELIN FENG1 Departments of 1Orthopedics and 2Breast Cancer Center, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, Hebei 050011; 3Department of Emergency, Hebei Medical University Second Affiliated Hospital, Shijiazhuang, Hebei 050000, P.R. China Received December 31, 2018; Accepted August 13, 2019 DOI: 10.3892/ol.2019.10936 Correspondence to: Dr Helin Feng, Department of Orthopedics, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Health Road, Shijiazhuang, Hebei 050011, P.R. China E‐mail: fenghelin0311@126.com *Contributed equally